Abstract

This study investigates the influence of large-scale flow features, including flow structure and velocity magnitude, on the early-burn period variability in a homogenous-charge spark-ignited engine fueled with premixed propane-air mixture. Particle image velocimetry and in-cylinder pressure measurement data from a previous study - were processed to enable simultaneous flow characterization and flame-front tracking as well as apparent heat-release analysis. By combining probability analysis of flame development with conditional sampling of fast and slow early-burn cycles using 10% fuel mass fraction burned, it is shown that an undesirable flow structure produces an asymmetric flame development at the initial flame growth period. This asymmetric flame structure persists through the whole initial-to-turbulent transition period until the flame becomes fully turbulent. The undesirable flow condition is characterized by large-scale convective flows near spark plug rather than flows that lead to increased flame spread in multiple directions. The simultaneous flow and flame characterization enables the quantifications of flame-front propagation speed, unburned fuel-air mixture velocity ahead of flame front and local burning velocity at flame surface. Here the local burning velocity is referred to as laminar or turbulent flame speed. A simplified approach is introduced to derive integrated values for these quantities per crank-angle-degree, enabling the quantitative comparison of the trend-wise difference in these integrated metrics between fast and slow early-burn cycles. It is revealed that for the transition period, the CCV in the velocity magnitude of unburned fuel-air mixture ahead of the flame front accounts for nearly 50% to the variability of flame propagation speed. The burning velocity provides the remaining source of the flame propagation variability in this period. The flame propagation variations in the initial flame growth and fully turbulent periods are smaller than those in the transition period and are primarily dependent on the variability of large-scale flow features.

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